Personality, habitat use, and their consequences for survival in North American red squirrels <i>Tamiasciurus hudsonicus</i>
Bibliographic record
Abstract
Personality affects many aspects of an individual's behaviour, life history and fitness, and has been shown to be moderately heritable in wild populations. Correlations between personality and risk‐taking that lead to life history tradeoffs could act to maintain variation in personality within a population, but this has not yet been tested. In this study, we used females from a marked population of North American red squirrels in Kluane, Yukon, to determine whether personality predicts risk‐taking in the wild, and whether these risk‐taking behaviours result in life history tradeoffs. We measured personality in open field and mirror image stimulation tests and extracted two traits, activity and aggressiveness, using principal component analysis and mixed model techniques. Using trapping records for individuals from February to September 2005, we obtained three measures of risk‐taking: the number of trapping events, the number of different trapping locations, and the maximum distance between the home territory and a trapping event. We used GLMs to determine whether the activity and aggressiveness of individuals are related to these risk‐taking behaviours, and found that active squirrels were trapped significantly more frequently and at a greater number of locations. There was also a significant interaction between activity and aggressiveness to affect the maximum capture distance. To determine if there are fitness tradeoffs associated with these risk‐taking behaviours, we examined female bequeathal behaviour and survival. Bequeathing a territory increases offspring probability of overwinter survival, and we found that an increasing number of trapping locations was associated with an increasing tendency to bequeath. Active females were less likely to survive until the following spring. Risk‐taking is therefore predicted by personality in this population, and they affect both survival and territorial bequeathal. These fitness tradeoffs may therefore lead to the maintenance of variation in personality.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".